Socioeconomic Status and Housework: Cultural Differences in Participation in Routine Housework in Japan, Canada, and the US
Bibliographic record
Abstract
The assumption about socioeconomic status (SES) and participation in housework are based on the empirical results in Western countries. As such, SES is assumed to work in a similar way in other regions as it does in the countries of the global north. This assumption can often lead to misguided interpretations of the effects of SES on housework participation in other cultural contexts. One such exception is Japan. We analyze time-use diaries from the American Time Use Survey for the period from 2003 to 2016, 1986-2010 Canadian General Social Survey, and the 2006 Japan Survey on Time Use and Leisure Activities (社会生活基本調査). Using the negative binomial regression, we test whether SES is associated with less time spent on housework as the outsourcing hypothesis predicts. The findings show that this hypothesis stands only for Canadian and American women, whereas married Japanese women are unlikely to reduce their participation in housework with the increase of their SES.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".